Results 191 to 200 of about 4,636,420 (247)
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Biometrics, 1999
Summary.Survival data stand out as a special statistical field. This paper tries to describe what survival data is and what makes it so special. Survival data concern times to some events. A key point is the successive observation of time, which on the one hand leads to some times not being observed so that all that is known is that they exceed some ...
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Summary.Survival data stand out as a special statistical field. This paper tries to describe what survival data is and what makes it so special. Survival data concern times to some events. A key point is the successive observation of time, which on the one hand leads to some times not being observed so that all that is known is that they exceed some ...
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ANALYZING TRANSPLANT SURVIVAL DATA
Transplantation, 1986Stratified proportional hazards regression is described as a method of estimating multifactorially preoperative factor effects on graft survival--and, at the same time, making due allowances for unknown transplant-center-specific influences. The multifactorial aspect of the method overcomes the biases inherent in analyzing transplant survival data one ...
W R, Gilks, S M, Gore, B A, Bradley
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2005
Abstract Over the last 30 years there has been a rapid development of probability models and statistical analysis for technological and medical survival data. Many studies have been made of the length of life or of periods of remission of animal or human subjects being treated for serious diseases.
Murray Aitkin, Brain Francis, John Hinde
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Abstract Over the last 30 years there has been a rapid development of probability models and statistical analysis for technological and medical survival data. Many studies have been made of the length of life or of periods of remission of animal or human subjects being treated for serious diseases.
Murray Aitkin, Brain Francis, John Hinde
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2009
Abstract Over the last 30 years there has been a rapid development of probability models and statistical analysis for technological and medical survival data. Many studies have been made of the length of life or of periods of remission of animal or human subjects being treated for serious diseases.
Murray Aitkin +3 more
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Abstract Over the last 30 years there has been a rapid development of probability models and statistical analysis for technological and medical survival data. Many studies have been made of the length of life or of periods of remission of animal or human subjects being treated for serious diseases.
Murray Aitkin +3 more
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Analysis of lognormal survival data
Mathematical Biosciences, 1997The failure rate and the mean residual life function (MRLF) of a lognormal distribution are known to be nonmonotonic. It is of interest to study the point at which the monotonicity changes (the change point). In this article we study the change points of the failure rate and the MRLF for the lognormal distribution.
Gupta, Ramesh C. +2 more
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A New Bayesian Model for Survival Data with a Surviving Fraction
Journal of the American Statistical Association, 1999We consider Bayesian methods for right-censored survival data for populations with a surviving (cure) fraction. We propose a model that is quite different from the standard mixture model for cure rates. We provide a natural motivation and interpretation of the model and derive several novel properties of it.
Ming-Hui, Chen +2 more
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Multivariate Survival Data With Censoring
2008We define a new class of models for multivariate survival data, in continuous time, based on a number of cumulative hazard functions, along the lines of our family of models for correlated survival data in discrete time [Gross and Huber-Carol (2000, 2002)]. This family is an alternative to frailty and copula models.
Huber, Catherine, Gross, Shulamith
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Prediction intervals for survival data
Statistics in Medicine, 1983AbstractThis paper concerns large sample prediction intervals for the survival times of a future sample based on an initial sample of censored survival data. Simple procedures are developed for obtaining non‐parametric and exponential prediction intervals for the future sample quantiles; the non‐parametric interval results from inversion of an ...
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